The function apply Kalman smoother to compute smoothed values of the state vectors, together with their variance/covariance matrices.
1 2 3 4 5
an object used to select a method.
futher arguments passed to or from other methods.
an object of class
The default method returns means and variances of the smoothing
distribution for a data vector (or matrix)
y and a model
dlmSmooth.dlmFiltered produces the same output based on a
dlmFiltered object, typically one produced by a call to
The calculations are based on the singular value decomposition (SVD) of the relevant matrices. Variance matrices are returned in terms of their SVD.
A list with components
Time series (or matrix) of smoothed values of the state vectors. The series starts one time unit before the first observation.
The observation variance
mod must be nonsingular.
Giovanni Petris GPetris@uark.edu
Zhang, Y. and Li, X.R., Fixed-interval smoothing algorithm
based on singular value decomposition, Proceedings of the 1996
IEEE International Conference on Control Applications.
Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. http://www.jstatsoft.org/v36/i12/.
Petris, Petrone, and Campagnoli, Dynamic Linear Models with R, Springer (2009).
dlm for a description of dlm objects,
dlmSvd2var to obtain a variance matrix from its SVD,
dlmFilter for Kalman filtering,
dlmMLE for maximum likelihood estimation, and
dlmBSample for drawing from the posterior distribution
of the state vectors.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.